etree.parallel_map

etils.etree.parallel_map(

map_fn: Callable[[...], etils.etree.tree_utils._Tout],

*trees: Any | list[etils.etree.typing._T | list[Tree] | tuple[Tree, ...] | dict[str, Tree]] | tuple[etils.etree.typing._T | list[Tree] | tuple[Tree, ...] | dict[str, Tree], ...] | dict[str, etils.etree.typing._T | list[Tree] | tuple[Tree, ...] | dict[str, Tree]],

num_threads: int | None = None,

progress_bar: bool = False,

is_leaf: collections.abc.Callable[[Any], bool] | None = None,

) → etils.etree.tree_utils._Tout | list[etils.etree.typing._T | list[Tree] | tuple[Tree, ...] | dict[str, Tree]] | tuple[etils.etree.typing._T | list[Tree] | tuple[Tree, ...] | dict[str, Tree], ...] | dict[str, etils.etree.typing._T | list[Tree] | tuple[Tree, ...] | dict[str, Tree]]

Same as tree.map_structure but apply map_fn in parallel.

Parameters:

• map_fn – Worker function

• *trees – Nested input to pass to the map_fn

• num_threads – Number of workers (default to CPU count * 5)

• progress_bar – If True, display a progression bar.

• is_leaf – Don’t recurse into leaf if is_leaf(node) is True

Returns:

The nested structure after map_fn has been applied.